经济学院知识库

   近年来，气候变化问题受到世界各国的广泛关注，联合国政府间气候变化专门委员会 IPCC 颁布了一系列纲领性文件以推进全球温室气体减排工作。2018 年10月发布的特别报告中明确要求在2050年左右达到“净零排放”。为了实现这一目标，各国开始大力发展低碳经济，加快推进碳减排步伐。畜牧业作为国民经济重要的产业部门，为人类提供日常生活所需产品的同时，其生产过程也产生了大量的温室气体。因此，畜牧业碳排放问题得到了学者们的广泛关注，实现畜牧业生产低碳转型迫在眉睫。西北五省（区）是畜牧业生产的重点区域，由此产生的碳排放量也不容小觑。由此，本文通过开展该地区畜牧业碳排放的动态变化及影响因素研究，以期为协调生态环境保护和经济发展提供必要的参考依据。

   本文首先系统梳理了相关文献，依据 IPCC 公布的碳因子系数完成了对西北地区2000-2020年间畜牧业碳排放量的测度，使用 LMDI 模型分析了畜牧业碳排放的影响因素，在此基础上，利用 GTWR 模型分析其时空动态变化。研究结果表明：（1）西北地区畜牧业碳排放量呈逐年上升的趋势，其中新疆碳排放量最大，最大值为2225.67万吨，宁夏最小，最小值为244.99万吨。碳排放强度整体呈下降趋势，各省份间强度差距逐渐缩小。（2）生产效率因素对畜牧业碳强度均表现出负向抑制作用；人口规模因素对宁夏、陕西、青海、新疆表现出正向促进作用，对甘肃表现出负向抑制作用；结构因素对宁夏、陕西、甘肃、新疆起正向促进作用，对青海既有正向促进又有负向抑制，在不同年份表现不同。经济因素对各省畜牧业碳排放强度均具有正向促进作用。（3）经济发展水平的回归系数均为负值，表明经济水平的提升明显抑制了畜牧业碳排放的增加；畜牧业产业结构的回归系数在大多数年份表现为正值，表明牧业在农业中的比重增加会对畜牧业碳排放呈现促进作用；城镇化水平的回归系数在不同省份不同年份之间表现不同，宁夏和青海的城镇化水平与畜牧业碳排放强度呈正相关关系，新疆的城镇化水平与畜牧业碳排放强度呈负相关关系，陕西和甘肃的城镇化水平与畜牧业碳排放强度由负相关关系转为正相关关系。

     In recent years, the issue of climate change has attracted wide attention from all countries in the world. The United Nations Intergovernmental Panel on Climate Change (IPCC) has issued a series of programmatic documents to promote global greenhouse gas emission reduction. A special report released in October 2018 explicitly called for "net zero emissions" by around 2050. In order to achieve this goal, countries began to vigorously develop low-carbon economy and accelerate the pace of carbon emission reduction. Animal husbandry, as an important industrial sector of national economy, not only provides products needed for human daily life, but also produces a lot of greenhouse gases in its production process. Therefore, the issue of carbon emissions in animal husbandry has been widely concerned by scholars, and it is urgent to realize the low-carbon transformation of animal husbandry production. The northwest is a key area for livestock production, and the resulting carbon emissions cannot be underestimated. Therefore, this paper studies the dynamic changes and influencing factors of carbon emissions from animal husbandry in Northwest China, in order to provide necessary reference for the coordination of ecological environmental protection and economic development.

     Firstly, this paper systematically reviewed relevant literature and measured the carbon emissions of animal husbandry in Northwest China during 2000-2020 according to the carbon factor coefficient published by IPCC. LMDI model was used to analyze the influencing factors of animal husbandry carbon emissions. On this basis, the GTWR model was used to analyze the temporal and spatial dynamic changes. The results showed that: (1) Carbon emissions from animal husbandry in Northwest China showed an increasing trend year by year, among which Xinjiang had the largest carbon emissions, with a maximum value of 22.2567 million tons, and Ningxia had the smallest carbon emissions, with a minimum value of 2.449 million tons. The overall carbon emission intensity showed a downward trend, and the intensity gap among provinces gradually narrowed. (2) Production efficiency factors had negative inhibitory effects on carbon intensity of animal husbandry; The population size factor has a positive promoting effect on Ningxia, Shaanxi, Qinghai and Xinjiang, and a negative inhibiting effect on Gansu. The structural factors had a positive promoting effect on Ningxia, Shaanxi, Gansu and Xinjiang, and had both positive promoting and negative inhibiting effect on Qinghai, which showed different performance in different years. Economic factors have positive promoting effect on carbon emission intensity of animal husbandry in provinces. (3) The regression coefficients of economic development level were all negative, indicating that the improvement of economic level significantly inhibited the increase of carbon emissions from animal husbandry; The regression coefficient of animal husbandry industrial structure was positive in most years, indicating that the increasing proportion of animal husbandry in agriculture would promote the carbon emission of animal husbandry. The regression coefficient of urbanization level is different in different provinces and different years. The urbanization level of Ningxia and Qinghai is positively correlated with the carbon emission intensity of animal husbandry; the urbanization level of Xinjiang is negatively correlated with the carbon emission intensity of animal husbandry; the urbanization level of Shaanxi and Gansu is positively correlated with the carbon emission intensity of animal husbandry from negative correlation.